[2005.01643] Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
In this tutorial article, we aim to provide the reader with the conceptual tools needed to get started on research on offline reinforcement learning algorithms: reinforcement learning algorithms that utilize previously…
\stackMath Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine 1,2 , Aviral Kumar 1 , George Tucker 2 , Justin Fu 1 1 UC Berkeley, 2 Google Research, Brain Team Abstract In this tutorial article, we aim to provide the reader with the conceptual tools needed to get started on research on offline reinforcement learning algorithms: reinforcement learning algorithms that utilize previously collected data, without additional online data collection. Offline reinforcement learning algorithms hold tremendous promise for making it possible to turn large dat
related reading
- A (Long) Peek into Reinforcement Learning | Lil'Loglilianweng.github.io
- 2109.10813.pdfarxiv.org
- [2103.06326] S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learningarxiv.org
- [2307.04354] Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Dataar5iv.labs.arxiv.org
- Exploration for the Efficient Deployment of Reinforcement Learning Agentsopenreview.net
- [2204.05618] When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning?ar5iv.labs.arxiv.org
- Reinforcement Learning in Newcomblike Problemsproceedings.neurips.cc
- Should I Use Offline RL or Imitation Learning? – The Berkeley Artificial Intelligence Research Blogbair.berkeley.edu
- RL_Notes__final_.pdfjubayer-ibn-hamid.github.io
- [2406.09329] Is Value Learning Really the Main Bottleneck in Offline RL?ar5iv.labs.arxiv.org
- [1709.06560] Deep Reinforcement Learning that Mattersarxiv.org
- [2006.03647] Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimizationar5iv.labs.arxiv.org